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+0.09285909768549327 +0.07829942316784644 +0.09509340906137309 +0.07175162491982634 +-0.0009214803210092493 +0.14897475711647834 +0.049099677731036406 +0.020152095828829375 +0.0886303087826723 +0.1549458236184521 +0.15060394586901393 +0.004304750849741246 +0.021468918448934282 +0.02708680477941361 +0.13364621781635322 +0.15099037733832943 +0.13626927161216384 +0.07748959126858523 +0.06638101631405191 +0.010870710774564474 +0.08978071553557576 +0.0896024752947735 +-0.05870767900502527 +0.033639925550890126 +0.142727157133816 +0.14744870643362284 +0.0820522033978065 +0.23554948851442403 diff --git a/dev0_rmse.txt b/dev0_rmse.txt index edfd3ea..f80b4a0 100644 --- a/dev0_rmse.txt +++ b/dev0_rmse.txt @@ -1 +1 @@ -1013603084.8408571 \ No newline at end of file +1165319253.2984157 \ No newline at end of file diff --git a/main.py b/main.py index f6a7e4a..3bb0977 100644 --- a/main.py +++ b/main.py @@ -4,38 +4,33 @@ from sklearn.linear_model import LinearRegression from sklearn.metrics import mean_squared_error import numpy as np -df = pd.read_csv("train/train.tsv", header=None, sep="\t", error_bad_lines=False) -dev0 = pd.read_csv("dev-0/in.tsv", header=None, sep="\t", error_bad_lines=False) -testA = pd.read_csv("test-A/in.tsv", header=None, sep="\t", error_bad_lines=False) -expected = pd.read_csv("dev-0/expected.tsv", header=None, sep="\t", error_bad_lines=False) +df = pd.read_csv("train/train.tsv", header=None, sep="\t", error_bad_lines=False, names=['price', 'mileage', 'year', + 'brand', 'engineType', + 'engineCapacity']) +dev0 = pd.read_csv("dev-0/in.tsv", header=None, sep="\t", error_bad_lines=False, names=['mileage', 'year', + 'brand', 'engineType', + 'engineCapacity']) +testA = pd.read_csv("test-A/in.tsv", header=None, sep="\t", error_bad_lines=False, names=['mileage', 'year', + 'brand', 'engineType', + 'engineCapacity']) +expected = pd.read_csv("dev-0/expected.tsv", header=None, sep="\t", error_bad_lines=False, names=['price']) -all_df = df.copy() -test_dev0 = dev0.copy() -test_dev0.insert(0, "dum", 0, True) -test_dev0 = test_dev0.rename(columns={"dum": 0, 0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6}) -all_df = all_df.append(test_dev0, ignore_index=True) +df = df[['price', 'year', 'mileage', 'engineCapacity']] -test_testA = testA.copy() -test_testA.insert(0, "dum", 0, True) -test_testA = test_testA.rename(columns={"dum": 0, 0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6}) -all_df = all_df.append(test_testA, ignore_index=True) -all_df = pd.get_dummies(all_df, columns=[3, 4]) +min_val = np.min(df) +max_val = np.max(df) +df = (df - min_val) / (max_val - min_val) -min_val = np.min(all_df) -max_val = np.max(all_df) -all_df = (all_df - min_val) / (max_val - min_val) - -dummy_df = all_df[:len(df)] -dummy_dev0 = all_df[len(df):len(df) + len(dev0)] -dummy_testA = all_df[len(df) + len(dev0):] - -X = dummy_df[dummy_df.columns[1:]] -Y = dummy_df[dummy_df.columns[:1]] +Y = df[['price']] +X = df[['year', 'mileage', 'engineCapacity']] model = LinearRegression().fit(X, Y) -predicted_dev0 = model.predict(dummy_dev0[dummy_dev0.columns[1:]]) -predicted_testA = model.predict(dummy_testA[dummy_testA.columns[1:]]) +dev0 = (dev0[['year', 'mileage', 'engineCapacity']] - min_val) / (max_val - min_val) +testA = (testA[['year', 'mileage', 'engineCapacity']] - min_val) / (max_val - min_val) + +predicted_dev0 = model.predict(dev0[['year', 'mileage', 'engineCapacity']]) +predicted_testA = model.predict(testA[['year', 'mileage', 'engineCapacity']]) with open("dev-0/out.tsv", "w") as file: for pred in predicted_dev0: @@ -45,15 +40,18 @@ with open("test-A/out.tsv", "w") as file: for pred in predicted_testA: file.write(str(pred[0]) + "\n") + predicted_denormalized = [] for pred in predicted_dev0: - predicted_denormalized.append(pred[0] * (max_val[0] - min_val[0]) + min_val[0]) + denorm = pred[0] * (max_val[0] - min_val[0]) + min_val[0] + predicted_denormalized.append(denorm) predicted_denormalized = DataFrame(predicted_denormalized, columns=['pred']) error = mean_squared_error(expected, predicted_denormalized) for exp, pred in zip(expected.values, predicted_denormalized.values): print(exp, pred) - + f = open("dev0_rmse.txt", "w") f.write(str(error)) -f.close() \ No newline at end of file +f.close() +print(error) \ No newline at end of file diff --git a/test-A/out.tsv b/test-A/out.tsv index eb46b36..e718395 100644 --- a/test-A/out.tsv +++ b/test-A/out.tsv @@ -1,1000 +1,1000 @@ -0.0398712158203125 -0.03961181640625 -0.0081787109375 --0.008331298828125 -0.0478515625 -0.02728271484375 -0.0636444091796875 -0.02032470703125 -0.18865966796875 -0.073974609375 --0.065032958984375 -0.07843017578125 --0.015869140625 -0.0533599853515625 --0.002685546875 -0.0404205322265625 -0.0571746826171875 -0.118011474609375 -0.0555572509765625 -0.01812744140625 -0.1125946044921875 -0.0089874267578125 --0.0027008056640625 -0.09515380859375 --0.0116729736328125 -0.0307769775390625 -0.056488037109375 -0.096710205078125 -0.2142333984375 -0.0824432373046875 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